Keywords: Cartilage, Quantitative Imaging
Motivation: Standardizing imaging parameters to improve T2 repeatability in osteoarthritis is increasingly prioritized, given the subtle T2 changes in early OA. Major MRI vendors widely implement deep learning reconstruction (DLR) to enhance resolution or reduce scan time while maintaining SNR.
Goal(s): In this work, we evaluate the influence of resolution and DLR-denoising on quantitative T2 mapping using quantitative double-echo in steady-state (qDESS).
Approach: Knee cartilage qDESS T2 scan-rescan repeatability was performed in 10 healthy patients using 4 different resolutions and reconstructed with and without DLR-denoising.
Results: Unexpectedly, we observed higher repeatability with increasing resolution and no positive effect of DLR-denoising.
Impact: This study underscores the importance of investigating the role of imaging parameters for qDESS T2 repeatability. With our setting, repeatability increased with resolution, which was unexpected. Contrary to current implementation trends, DLR-denoising did not positively impact T2 reproducibility.
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