Muscle diseases commonly have clinical presentations of inflammation, fat infiltration, fibrosis, and atrophy. However, the results of existing laboratory tests and clinical presentations are not well correlated. Advanced quantitative MRI techniques may allow the assessment of myo-pathological changes in a sensitive and objective manner. To progress towards this goal, an array of quantitative MRI protocols was implemented for human thigh muscles; their reproducibility was assessed; and the statistical relationships among parameters were determined. These quantitative methods included fat/water imaging, multiple spin-echo T2 imaging (with and without fat signal suppression, FS), selective inversion recovery for T1 and quantitative magnetization transfer (qMT) imaging (with and without FS), and diffusion tensor imaging. Data were acquired at 3.0 T from nine healthy subjects. To assess the repeatability of each method, the subjects were re-imaged an average of 35 days later. Pre-testing lifestyle restrictions were applied to standardize physiological conditions across scans. Strong between-day intra-class correlations were observed in all quantitative indices except for the macromolecular-to-free water pool size ratio (PSR) with FS, a metric derived from qMT data. Two-way analysis of variance revealed no significant between-day differences in the mean values for any parameter estimate. The repeatability was further assessed with Bland-Altman plots, and low repeatability coefficients were obtained for all parameters. Among-muscle differences in the quantitative MRI indices and inter-class correlations among the parameters were identified. There were inverse relationships between fractional anisotropy (FA) and the second eigenvalue, the third eigenvalue, and the standard deviation of the first eigenvector. The FA was positively related to the PSR, while the other diffusion indices were inversely related to the PSR. These findings support the use of these T1 , T2 , fat/water, and DTI protocols for characterizing skeletal muscle using MRI. Moreover, the data support the existence of a common biophysical mechanism, water content, as a source of variation in these parameters.
Copyright © 2014 John Wiley & Sons, Ltd.