Purpose: In addition to less frequent and more comprehensive tests, quality assurance (QA) protocol for a magnetic resonance imaging (MRI) scanner may include cursory daily or weekly phantom checks to verify equipment constancy. With an automatic image analysis workflow, the daily QA images can be further used to study scanner baseline performance and both long- and short-term variations in image quality. With known baselines and variation profiles, automatic error detection can be employed.

Approach: Four image quality parameters were followed for 17 MRI scanners over six months: signal-to-noise ratio (SNR), image intensity uniformity, ghosting artifact, and geometrical distortions. Baselines and normal variations were determined. An automatic detection of abnormal QA images was compared with image deviations visually detected by human observers.

Results: There were significant inter-scanner differences in the QA parameters. In some cases, the results exceeded commonly accepted tolerances. Scanner field strengths, or a unit being stationary versus mobile, did not have a clear relationship with the QA results.

Conclusions: The variations and baseline levels of image QA parameters can differ significantly between MRI scanners. Scanner specific error thresholds based on parameter means and standard deviations are a viable option for detecting abnormal QA images.