Vendor-neutral sequences (VENUS) and fully transparent workflows improve inter-vendor reproducibility of quantitative MRI

Abstract

AbstractPurposeWe developed a transparent end-to-end qMRI workflow that starts with a vendor-neutral acquisition and tested the hypothesis that vendor-neutral sequences (VENUS) decrease inter-vendor variability of T1, MTR and MTsat measurements.MethodsWe developed and deployed a vendor-neutral 3D spoiled gradient-echo (SPGR) sequence on three clinical scanners by two MRI vendors and acquired T1 maps on the NIST phantom, as well as T1, MTR and MTsat maps in three healthy participants. We performed hierarchical shift function analysis in vivo to characterize the differences between scanners when VENUS is used instead of commercial vendor implementations. Inter-vendor deviations were compared for statistical significance to test the hypothesis.ResultsIn the NIST phantom, VENUS reduced inter-vendor differences from 8 - 19.4% to 0.2 - 5% with an overall accuracy improvement, reducing ground truth T1 deviation from 7 - 11% to 0.2 - 4%. In vivo we found that the variability between vendors is significantly reduced (p = 0.015) for all maps (T1, MTR and MTsat) using VENUS.ConclusionWe conclude that vendor-neutral workflows are feasible and compatible with clinical MRI scanners. The significant reduction of inter-vendor variability using VENUS has important implications for qMRI research and for the reliability of multicenter clinical trials.