A novel approach to evaluate spatial resolution of MRI clinical images for optimization and standardization of breast screening protocols.
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PURPOSE: Stringent quality assurance is required in MRI breast screening to ensure that different scanners and imaging protocols reach similar diagnostic performance. The authors propose a methodology, based on power spectrum analysis (PSA), to evaluate spatial resolution in clinical images. To demonstrate this approach, the authors have retrospectively compared two MRI sequences commonly employed in breast screening. METHODS: In a novel approach to PSA, spatial frequency response curves (SFRCs) were extracted from the images. The SFRC characterizes spatial resolution describing the spatial frequency content of an image over a range of frequencies. Verification of the SFRCs was performed on MRI images of Eurospin agarose gel tubes acquired with different resolution settings. SFRCs of volunteer and patient images obtained with two clinical MRI sequences were then compared. The two sequences differed primarily in k-space coverage pattern, which was either radial (RAD) or linear (LIN). RESULTS: The computed SFRCs were able to demonstrate the differences between RAD and LIN sequences in relatively small groups of subjects. The curves showed a similar pattern of decay in both volunteer and patient images, indicating that the spatial frequency response is mainly determined by the imaging protocol and not by intersubject anatomical differences. The LIN protocol produced images with increased sharpness; this was reflected in the corresponding SFRCs, which showed a higher content of spatial frequencies associated with image details. CONCLUSIONS: The SFRC can provide an objective assessment of the presence of spatial details in the image and represent a useful quality assurance tool in the evaluation of different breast screening protocols. With a reference image, a comparative analysis of the SFRCs could ensure that equivalent image quality is achieved across different scanners and sites.
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Image Processing, Computer-Assisted
Magnetic Resonance Imaging
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Med Phys, 2016, 43 (12), pp. 6354 - ?