Quantitative muscle analysis in facioscapulohumeral muscular dystrophy using whole‐body fat‐referenced MRI: Protocol development, multicenter feasibility, and repeatability Journal Articles uri icon

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abstract

  • AbstractIntroduction/AimsFunctional performance tests are the gold standard to assess disease progression and treatment effects in neuromuscular disorders. These tests can be confounded by motivation, pain, fatigue, and learning effects, increasing variability and decreasing sensitivity to disease progression, limiting efficacy assessment in clinical trials with small sample sizes. We aimed to develop and validate a quantitative and objective method to measure skeletal muscle volume and fat content based on whole‐body fat‐referenced magnetic resonance imaging (MRI) for use in multisite clinical trials.MethodsSubjects aged 18 to 65 years, genetically confirmed facioscapulohumeral muscular dystrophy 1 (FSHD1), clinical severity 2 to 4 (Ricci's scale, range 0–5), were enrolled at six sites and imaged twice 4–12 weeks apart with T1‐weighted two‐point Dixon MRI covering the torso and upper and lower extremities. Thirty‐six muscles were volumetrically segmented using semi‐automatic multi‐atlas‐based segmentation. Muscle fat fraction (MFF), muscle fat infiltration (MFI), and lean muscle volume (LMV) were quantified for each muscle using fat‐referenced quantification.ResultsSeventeen patients (mean age ± SD, 49.4 years ±13.02; 12 men) were enrolled. Within‐patient SD ranged from 1.00% to 3.51% for MFF and 0.40% to 1.48% for MFI in individual muscles. For LMV, coefficients of variation ranged from 2.7% to 11.7%. For the composite score average of all muscles, observed SDs were 0.70% and 0.32% for MFF and MFI, respectively; composite LMV coefficient of variation was 2.0%.DiscussionWe developed and validated a method for measuring skeletal muscle volume and fat content for use in multisite clinical trials of neuromuscular disorders.

authors

  • Widholm, Per
  • Ahlgren, André
  • Karlsson, Markus
  • Romu, Thobias
  • Tawil, Rabi
  • Wagner, Kathryn R
  • Statland, Jeffrey M
  • Wang, Leo H
  • Shieh, Perry B
  • van Engelen, Baziel GM
  • Cadavid, Diego
  • Ronco, Lucienne
  • Odueyungbo, Adefowope
  • Jiang, John G
  • Mellion, Michelle L
  • Dahlqvist Leinhard, Olof

publication date

  • August 2022