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

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 s...

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Publicado en:Muscle & Nerve Vol. 61; no. 5; pp. 600 - 608
Autores principales: Müller, Madlaine, Dohrn, Maike F., Romanzetti, Sandro, Gadermayr, Michael, Reetz, Kathrin, Krämer, Nils A., Kuhl, Christiane, Schulz, Jörg B., Gess, Burkhard
Formato: Journal Article
Publicado: Wiley-Blackwell May2020
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2020
      vid: 61
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1002/mus.26827
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        atl: Semi-automated volumetry of MRI serves as a biomarker in neuromuscular patients.
      aug:
        au:
          Müller, Madlaine
          Dohrn, Maike F.
          Romanzetti, Sandro
          Gadermayr, Michael
          Reetz, Kathrin
          Krämer, Nils A.
          Kuhl, Christiane
          Schulz, Jörg B.
          Gess, Burkhard
        affil: Department of Neurology, University Hospital Aachen, Aachen, Germany
      sug:
        subj:
          Peripheral Nervous System Diseases
          Software
          Muscular Diseases
          Muscle, Skeletal
          Magnetic Resonance Imaging
          Diabetic Neuropathies Pathology
          Case Control Studies
          Charcot-Marie-Tooth Disease
          Retrospective Design
          Body Weights and Measures
          Charcot-Marie-Tooth Disease Pathology
          Polymyositis Pathology
          Muscle, Skeletal Pathology
          Myositis Pathology
          Peripheral Nervous System Diseases Pathology
          Muscular Diseases Pathology
          Diabetic Neuropathies
          Myositis, Inclusion Body Pathology
          Polyradiculoneuritis Pathology
          Muscular Dystrophy Pathology
          Female
          Polymyositis
          Image Processing, Computer Assisted
          Male
          Muscular Dystrophy
          Automation
          Polyradiculoneuritis
          Myositis
          Adult
          Myositis, Inclusion Body
          Middle Age
          Aged
          Scales
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Female
          Male
      ab: 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.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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