An Automated Method for Quality Control in MRI Systems: Methods and Considerations

Angeliki C Epistatou,Ioannis A Tsalafoutas,Konstantinos K Delibasis

doi:10.3390/jimaging6100111

Angeliki C Epistatou, Ioannis A Tsalafoutas + Show 1 more

Open Access

https://doi.org/10.3390/jimaging6100111

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Abstract

Objective: The purpose of this study was to develop an automated method for performing quality control (QC) tests in magnetic resonance imaging (MRI) systems, investigate the effect of different definitions of QC parameters and its sensitivity with respect to variations in regions of interest (ROI) positioning, and validate the reliability of the automated method by comparison with results from manual evaluations. Materials and Methods: Magnetic Resonance imaging MRI used for acceptance and routine QC tests from five MRI systems were selected. All QC tests were performed using the American College of Radiology (ACR) MRI accreditation phantom. The only selection criterion was that in the same QC test, images from two identical sequential sequences should be available. The study was focused on four QC parameters: percent signal ghosting (PSG), percent image uniformity (PIU), signal-to-noise ratio (SNR), and SNR uniformity (SNRU), whose values are calculated using the mean signal and the standard deviation of ROIs defined within the phantom image or in the background. The variability of manual ROIs placement was emulated by the software using random variables that follow appropriate normal distributions. Results: Twenty-one paired sequences were employed. The automated test results for PIU were in good agreement with manual results. However, the PSG values were found to vary depending on the selection of ROIs with respect to the phantom. The values of SNR and SNRU also vary significantly, depending on the combination of the two out of the four standard rectangular ROIs. Furthermore, the methodology used for SNR and SNRU calculation also had significant effect on the results. Conclusions: The automated method standardizes the position of ROIs with respect to the ACR phantom image and allows for reproducible QC results.

Highlights

Magnetic resonance imaging (MRI) is based on the nuclear magnetic resonance (NMR) physical phenomenon [1]
Methods, this study focuses on quality control (QC) result reproducibility problems, which may arise from variation in the position where regions of interest (ROI) are located with respect to the phantom and on the effect on the signal-to-noise ratio (SNR)
Images from only one QC were used, while for other systems, images from more than one QC test were utilized. These images were selected from a database of QC images, because two sequential acquisitions of the American College of Radiology (ACR) phantom with identical scanning parameters had been performed in each system the same day and with a time difference of about 5 min, something which was essential for SNR calculations using all methods that have been proposed

Summary

Introduction

Magnetic resonance imaging (MRI) is based on the nuclear magnetic resonance (NMR) physical phenomenon [1]. MRI systems do not use ionizing radiation but strong magnetic fields and radiofrequency electromagnetic radiation (RF pulses). The absence of ionizing radiation risks is the first reason why MRI is an attractive imaging option. The second is that, since the imaging principle of MRI is not based on X-ray attenuation but on the magnetization properties of tissues T1, T2, and T2*), completely different images than those acquired in CT are obtained. MRI provides information for both anatomical and functional characteristics of human tissues and by modifying the acquisition parameters different tissues and functional characteristics can be highlighted or suppressed, facilitating diagnosis. J. Imaging 2020, 6, 111; doi:10.3390/jimaging6100111 www.mdpi.com/journal/jimaging

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