再现性
组内相关
磁共振弥散成像
核医学
变异系数
医学
方差分析
数学
磁共振成像
统计
放射科
内科学
作者
Lara Schlaffke,Robert Rehmann,Marlena Rohm,Louise Otto,Alberto De Luca,Jedrzej Burakiewicz,Céline Baligand,Jithsa R. Monte,Chiel den Harder,Melissa T. Hooijmans,Aart J. Nederveen,Sarah Schlaeger,Dominik Weidlich,Dimitrios C. Karampinos,Anders Stouge,Michael Væggemose,Maria Grazia D’Angelo,Filippo Arrigoni,Hermien E. Kan,Martijn Froeling
摘要
The purpose of this study was to evaluate temporal stability, multi‐center reproducibility and the influence of covariates on a multimodal MR protocol for quantitative muscle imaging and to facilitate its use as a standardized protocol for evaluation of pathology in skeletal muscle. Quantitative T2, quantitative diffusion and four‐point Dixon acquisitions of the calf muscles of both legs were repeated within one hour. Sixty‐five healthy volunteers (31 females) were included in one of eight 3‐T MR systems. Five traveling subjects were examined in six MR scanners. Average values over all slices of water‐T2 relaxation time, proton density fat fraction (PDFF) and diffusion metrics were determined for seven muscles. Temporal stability was tested with repeated measured ANOVA and two‐way random intraclass correlation coefficient (ICC). Multi‐center reproducibility of traveling volunteers was assessed by a two‐way mixed ICC. The factors age, body mass index, gender and muscle were tested for covariance. ICCs of temporal stability were between 0.963 and 0.999 for all parameters. Water‐T2 relaxation decreased significantly ( P < 10 −3 ) within one hour by ~ 1 ms. Multi‐center reproducibility showed ICCs within 0.879–0.917 with the lowest ICC for mean diffusivity. Different muscles showed the highest covariance, explaining 20–40% of variance for observed parameters. Standardized acquisition and processing of quantitative muscle MRI data resulted in high comparability among centers. The imaging protocol exhibited high temporal stability over one hour except for water T2 relaxation times. These results show that data pooling is feasible and enables assembling data from patients with neuromuscular diseases, paving the way towards larger studies of rare muscle disorders.
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