A framework for validating open-source pulse sequences

Open-source pulse sequence programs offer an accessible and transparent approach to sequence development and deployment. However, a common framework for testing, documenting, and sharing open-source sequences is still needed to ensure sequence usability and repeatability. We propose and demonstrate such a framework by implementing two sequences, Inversion Recovery Spin Echo (IRSE) and Turbo Spin Echo (TSE), with PyPulseq, and testing them on a commercial 3 T scanner. We used the ACR and ISMRM/NIST phantoms for qualitative imaging and T₁/T₂ mapping, respectively. The qualitative sequences show good agreement with vendor-provided counterparts (mean Structural Similarity Index Measure (SSIM) = 0.810 for IRSE and 0.826 for TSE). Both sequences passed five out of the seven standard ACR tests, performing at similar levels to vendor counterparts. Compared to reference values, the coefficient of determination R² was 0.9946 for IRSE T₁ mapping and 0.9331 for TSE T₂ mapping. All sequences passed the scanner safety check for a 70 kg, 175 cm subject. The framework was demonstrated by packaging the sequences and sharing them on GitHub with data and documentation on the file generation, acquisition, reconstruction, and post-processing steps. The same sequences were tested at a second site using a 1.5 T scanner with the information shared. PDF templates for both sequence developers and users were created and filled.