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Updated: Dec 21, 2025

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Associations between magnetic resonance imaging and EMG findings in myopathies
Hans-Jonas Meyer1, Ilka Schneider2, Alexander Emmer2
1Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany.
Objectives:
Magnetic resonance imaging (MRI) is a cornerstone in diagnosis of myopathies. The present study sought to elucidate possible associations between electromyography (EMG) findings and histogram parameters derived from clinical MRI in myositis and other myopathies.
Materials And Methods:
Twenty six patients with myopathies were included in this retrospective study. Clinical MRI was performed with a 1.5T MRI scanner including T2- and T1-weighted images. EMG analysis was performed during clinical diagnostic workup. The histogram parameters of the MRI sequences were obtained of the same muscle, which was investigated with EMG.
Results:
Several correlations were identified between mean duration of the motor unit potentials (MUP) and histogram parameters derived from T1- and T2-weighted images. The highest for T1-weighted images was mode (r = -.73, P < .0001) and for T2-weighted images was p25 (r = -.57, P = .022). There were significant differences for several histogram parameters between muscles with pathological spontaneous activity and without. So, for T1-weighted images, the best discrimination was achieved with mean (P = .096), and for T2-weighted images for p10 (P = .05). Mean SI values derived from T1-weighted images achieved an AUC of 0.84 with a sensitivity of 0.81 and a specificity of 0.86 to discriminate patients with and without pathological spontaneous activity (PSA).
Conclusions:
The present study identified strong associations between histogram analysis derived from morphological MRI sequences and the duration of the MUP derived from EMG in myopathies strengthening the fact that both diagnostic modalities can reflect disease state in a similar fashion. Histogram parameters can predict muscles with PSA.
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