Effect of a Low-Rank Denoising Algorithm on Quantitative Magnetic Resonance Imaging-Based Measures of Liver Fat and Iron

Journal of Computer Assisted Tomography
Brian C AllenMustafa Bashir

Abstract

This study aimed to assess the effect of a low-rank denoising algorithm on quantitative magnetic resonance imaging-based measures of liver fat and iron. This was an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant, retrospective analysis of 42 consecutive subjects who were imaged at 3T using a multiecho gradient echo sequence that was reconstructed using the multistep adaptive fitting algorithm to obtain quantitative proton density fat fraction (PDFF) and R2* maps (original maps). A patch-wise low-rank denoising algorithm was then applied, and PDFF and R2* maps were created (denoised maps). Three readers independently rated the PDFF maps in terms of vessel and liver edge sharpness and image noise using a 5-point scale. Two other readers independently measured mean and standard deviation of PDFF and R2* values for the original and denoised maps; values were compared using intraclass correlation coefficients (ICCs) and mean difference analyses. Qualitatively, the denoised maps were preferred by all 3 readers based on image noise (P < 0.001) and by 2 of 3 readers based on vessel edge sharpness (P < 0.001-0.99). No reader had a significant preference regarding liver edge sharpness (...Continue Reading

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Citations

Feb 6, 2019·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Mark D DoesNoam Shemesh

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