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Magn Reson Imaging ; 92: 260-267, 2022 10.
Artículo en Inglés | MEDLINE | ID: mdl-35623416

RESUMEN

PURPOSE: To determine the accuracy, repeatability, and reproducibility of magnetic resonance imaging-based proton density fat fraction (MRI-PDFF) measurements of rotator cuff muscles between two readers and three different scanners. METHODS: Twenty-seven volunteers underwent serial shoulder MRI examinations of both left and right sides on one 1.5-T MRI scanner and two 3.0-T MRI scanners. Two independent readers measured muscular PDFF of the supraspinatus, infraspinatus/teres minor muscle, and subscapularis. MR spectroscopy-based proton density fat fraction (MRS-PDFF) was regarded as the reference standard for assessing accuracy. A "coffee break" examination method was used to test the repeatability of each scanner. Bland-Altman plots, Pearson correlation, and linear regression analysis were used to assess bias and linearity. The Wilcoxon signed-rank test and Friedman test were applied to evaluate repeatability and reproducibility. RESULTS: MRI-PDFF measurements indicated strong linearity (R2 = 0.749) and small bias (-0.18%) in comparison with the MRS-PDFF measurements. A very strong positive Pearson correlation (r = 0.955-0.986) between the PDFF estimates of the two repeat scans indicated excellent repeatability. The PDFF measurements showed high reproducibility, with a strong positive Pearson correlation (r = 0.668-0.698) and a small mean bias (-0.04 to -0.10%) across different scanners. CONCLUSION: MRI-PDFF measurements of rotator cuff muscles were highly accurate, repeatable, and reproducible across different readers and scanners, leading us to the conclusion that PDFF can be a reliable and robust quantitative imaging biomarker for longitudinal or multi-center studies.


Asunto(s)
Protones , Manguito de los Rotadores , Humanos , Hígado/patología , Imagen por Resonancia Magnética/métodos , Espectroscopía de Resonancia Magnética/métodos , Reproducibilidad de los Resultados , Manguito de los Rotadores/diagnóstico por imagen
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