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Assessing Functional Performance in the Mdx Mouse Model
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Modeling disease trajectory in Duchenne muscular dystrophy.

William D Rooney1, Yosef A Berlow2, William T Triplett2

  • 1From the Advanced Imaging Research Center (W.D.R., Y.A.B., I.A., E.O., B.M.), Department of Neurology (W.D.R., I.A., B.S.R., E.L.F.), Department of Biomedical Engineering (W.D.R.), Department of Behavioral Neuroscience (W.D.R., Y.A.B.), and Department of Pediatrics (B.S.R., E.L.F.), Oregon Health & Science University, Portland; Departments of Physical Therapy (W.T.T., S.C.F., R.J.W., H.A., C.S., D.J.L., K.V.), Statistics (S.C., M.J.D.), Physiology and Functional Genomics (A.B., G.A.W.), and Pharmacology & Therapeutics (H.L.S.), University of Florida, Gainesville; Department of Radiology (D.-J.W.) and Division of Neurology (G.T.), Children's Hospital of Philadelphia, PA; Department of Pediatrics (R.F.), Nemours Children's Hospital, Orlando, FL; and Shriners Hospital (B.S.R., E.L.F.), Portland, OR. rooneyw@ohsu.edu.

Neurology
|March 19, 2020
PubMed
Summary

Magnetic resonance biomarkers accurately track Duchenne muscular dystrophy (DMD) progression. This method aids in monitoring treatments and predicting functional outcomes in DMD patients.

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Area of Science:

  • Biomedical imaging
  • Neuromuscular disorders
  • Quantitative MRI

Background:

  • Duchenne muscular dystrophy (DMD) is a progressive genetic disorder characterized by muscle degeneration.
  • Noninvasive biomarkers are crucial for monitoring disease progression and treatment efficacy in DMD.

Purpose of the Study:

  • To quantify disease progression in Duchenne muscular dystrophy (DMD) using magnetic resonance (MR) biomarkers in leg muscles.
  • To establish a modeling approach for MR biomarkers to assess DMD progression and treatment effects.

Main Methods:

  • Prospective observational study involving 104 DMD patients and 51 controls, followed for up to 6 years.
  • Acquisition of MRI and magnetic resonance spectroscopy (MRS) biomarkers, including fat fractions (FF) and quantitative T2 (qT2) values.
  • Longitudinal data modeling using a nonlinear mixed-effects approach to analyze biomarker changes.

Main Results:

  • MRS FF and MRI qT2 values increased with DMD disease duration, with significant individual and inter-muscle variability.
  • The age of half-maximal muscle involvement (μ) was earlier in vastus lateralis than soleus and associated with loss-of-ambulation age.
  • Corticosteroid treatment showed a delay in μ, with greater effects on slower-progressing muscles.

Conclusions:

  • MRS FF and MRI qT2 are sensitive, noninvasive measures for tracking DMD progression.
  • Modeling these biomarkers aids in monitoring therapeutic effects (e.g., corticosteroids) and provides prognostic information.
  • This approach transforms MR biomarkers into understandable metrics for summarizing DMD progression at individual and population levels.