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. 2020 May;61(5):600-607.
doi: 10.1002/mus.26827. Epub 2020 Feb 17.

Semi-automated volumetry of MRI serves as a biomarker in neuromuscular patients

Madlaine Müller  1 , Maike F Dohrn  1 , Sandro Romanzetti  1 , Michael Gadermayr  2 , Kathrin Reetz  1   3 , Nils A Krämer  4 , Christiane Kuhl  4 , Jörg B Schulz  1   3 , Burkhard Gess  1
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Semi-automated volumetry of MRI serves as a biomarker in neuromuscular patients

Madlaine Müller et al. Muscle Nerve. 2020 May.

Abstract

Background: Muscle MRI is of increasing importance for neuromuscular patients to detect changes in muscle volume, fat-infiltration, and edema. We developed a method for semi-automated segmentation of muscle MRI datasets.

Methods: An active contour-evolution algorithm implemented within the ITK-SNAP software was used to segment T1-weighted MRI, and to quantify muscle volumes of neuromuscular patients (n = 65).

Results: Semi-automated compared with manual segmentation was shown to be accurate and time-efficient. Muscle volumes and ratios of thigh/lower leg volume were lower in myopathy patients than in controls (P < .0001; P < .05). We found a decrease of lower leg muscle volume in neuropathy patients compared with controls (P < .01), which correlated with clinical parameters. In myopathy patients, muscle volume showed a positive correlation with muscle strength (rleft = 0.79, pleft < .0001). Muscle volumes were independent of body mass index and age.

Conclusions: Our method allows for exact and time-efficient quantification of muscle volumes with possible use as a biomarker in neuromuscular patients.

Keywords: MR imaging; biomarker; muscle dystrophy; neuromuscular disorders; segmentation; thresholding.

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REFERENCES

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