Modeling disease trajectory in Duchenne muscular dystrophy

William D. Rooney, Yosef A. Berlow, William T. Triplett, Sean C. Forbes, Rebecca J. Willcocks, Dah Jyuu Wang, Ishu Arpan, Harneet Arora, Claudia Senesac, Donovan J. Lott, Gihan Tennekoon, Richard Finkel, Barry S. Russman, Erika L. Finanger, Saptarshi Chakraborty, Elliott O'Brien, Brendan Moloney, Alison Barnard, H. Lee Sweeney, Michael J. DanielsGlenn A. Walter, Krista Vandenborne

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


Objective: To quantify disease progression in individuals with Duchenne muscular dystrophy (DMD) using magnetic resonance biomarkers of leg muscles.MethodsMRI and magnetic resonance spectroscopy (MRS) biomarkers were acquired from 104 participants with DMD and 51 healthy controls using a prospective observational study design with patients with DMD followed up yearly for up to 6 years. Fat fractions (FFs) in vastus lateralis and soleus muscles were determined with 1H MRS. MRI quantitative T2 (qT2) values were measured for 3 muscles of the upper leg and 5 muscles of the lower leg. Longitudinal changes in biomarkers were modeled with a cumulative distribution function using a nonlinear mixed-effects approach.ResultsMRS FF and MRI qT2 increased with DMD disease duration, with the progression time constants differing markedly between individuals and across muscles. The average age at half-maximal muscle involvement () occurred 4.8 years earlier in vastus lateralis than soleus, and these measures were strongly associated with loss-of-ambulation age. Corticosteroid treatment was found to delay by 2.5 years on average across muscles, although there were marked differences between muscles with more slowly progressing muscles showing larger delay.ConclusionsMRS FF and MRI qT2 provide sensitive noninvasive measures of DMD progression. Modeling changes in these biomarkers across multiple muscles can be used to detect and monitor the therapeutic effects of corticosteroids on disease progression and to provide prognostic information on functional outcomes. This modeling approach provides a method to transform these MRI biomarkers into well-understood metrics, allowing concise summaries of DMD disease progression at individual and population identifier:NCT01484678.

Original languageEnglish (US)
Pages (from-to)E1622-E1633
Issue number15
StatePublished - Apr 14 2020

ASJC Scopus subject areas

  • Clinical Neurology


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