An Automatic Image Processing Workflow for Daily Magnetic Resonance Imaging Quality Assurance

The performance of magnetic resonance imaging (MRI) equipment is typically monitored with a quality assurance (QA) program. The QA program includes various tests performed at regular intervals. Users may execute specific tests, e.g., daily, weekly, or monthly. The exact interval of these measurements varies according to the department policies, machine setup and usage, manufacturer's recommendations, and available resources. In our experience, a single image acquired before the first patient of the day offers a low effort and effective system check. When this daily QA check is repeated with identical imaging parameters and phantom setup, the data can be used to derive various time series of the scanner performance. However, daily QA with manual processing can quickly become laborious in a multi-scanner environment. Fully automated image analysis and results output can positively impact the QA process by decreasing reaction time, improving repeatability, and by offering novel performance evaluation methods. In this study, we have developed a daily MRI QA workflow that can measure multiple scanner performance parameters with minimal manual labor required. The daily QA system is built around a phantom image taken by the radiographers at the beginning of day. The image is acquired with a consistent phantom setup and standardized imaging parameters. Recorded parameters are processed into graphs available to everyone involved in the MRI QA process via a web-based interface. The presented automatic MRI QA system provides an efficient tool for following the short- and long-term stability of MRI scanners.