Elsevier

Neuromuscular Disorders

Volume 25, Issue 9, September 2015, Pages 679-685
Neuromuscular Disorders

Quantitative muscle MRI: A powerful surrogate outcome measure in Duchenne muscular dystrophy

https://doi.org/10.1016/j.nmd.2015.05.006Get rights and content

Highlights

  • Powerful outcome measures for clinical trials in neuromuscular disorders are needed.

  • In this study the effect size of qMRI was greater than that of physical scales (MFM).

  • Sample size estimations for qMRI were up to 17 fold smaller compared to the MFM.

  • QMRI is safe, independent of ambulatory abilities and well tolerated by children.

Abstract

In muscular dystrophies quantitative muscle MRI (qMRI) detects disease progression more sensitively than clinical scores. This prospective one year observational study compared qMRI with clinical scores in Duchenne muscular dystrophy (DMD) to investigate if qMRI can serve as a surrogate outcome measure in clinical trials. In 20 DMD patients the motor function measure (MFM) total and subscores (D1–D3) were done for physical examination, and the fat fraction (MFF) of thigh muscle qMRI was obtained using the two-point Dixon method. Effect sizes (ES) were calculated for all measures. Sample size estimation (SS) was done modelling assumed treatment effects. Ambulant patients <7 years at inclusion improved in the MFM total and D1 score (ES 1.1 and 1.0). Ambulant patients >7 years (highest ES in the MFM D1 subscore (1.2)), and non-ambulant patients (highest ES in the total MFM score (0.7)) worsened. In comparison the ES of QMRI was much larger, e.g. SS estimations for qMRI data were up to 17 fold smaller compared to the MFM total score and up to 7 fold to the D1 subscore, respectively. QMRI shows pathophysiological changes in DMD and might serve as a surrogate outcome measure in clinical trials.

Introduction

Duchenne muscular dystrophy (DMD) is an orphan disease affecting 1 in 3500–6000 male births. Planning clinical trials in DMD is challenging for the following reasons: a) disease progression doesn't follow a linear course when physical abilities are measured; longitudinal studies using clinical measurements showed an improvement of gross and fine motor function up to the age of seven, then a plateau phase up to the age of ten and then a phase of rapid decline during which free ambulation is lost [1], [2] ; b) DMD is a rare disease making clinical trials difficult; c) clinical assessment is dependent on cooperation and often differs between ambulant and non-ambulant patients.

Therefore outcome measures are essential that are sensitive to measure treatment effects even in small and highly heterogeneous patient populations and are less likely biased than clinical measurements. In contrast to functional scores obtained by physical assessment, quantitative MRI (qMRI) is less dependent on patient collaboration or form on the day of testing. When done by trained staff and adequate scanning protocols, excellent reproducibility of qMRI was demonstrated in healthy volunteers as well as in patients [3], [4], and was more sensitive than clinical evaluation and visual analysis of MRI scans to detect disease progression [5], [6]. Thus, qMRI techniques are increasingly used to study disease progression in neuromuscular disorders, especially in patients with DMD [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16].

The Motor function measure (MFM) is recommended as an efficacy measurement by the European Medicines Agency for clinical trials in ambulant and non-ambulant children with neuromuscular disorders [17]. This scale has three dimensions: standing and transfers (D1), axial and proximal motor function (D2), and distal motor function (D3) as well as a total (MFM total) scores that is calculated from the D1, D2 and D3 subscores. It shows high correlation to age as well as to qMRI measures of fatty degeneration [2], [5], [14].

The aim of the present study was to compare disease progression measured by the MFM and qMRI longitudinally to evaluate if qMRI could be used as a surrogate outcome measure in clinical studies in DMD and other myopathies.

Section snippets

Patients and clinical assessment

Twenty patients with genetically confirmed DMD who participated in a transversal study on muscle MRI [14] were reenrolled for this additional longitudinal evaluation. According to the age at baseline the following patient sub-groups were formed: Group 1: patients <7 years of age; group 2: ambulant patients >7 years of age; group 3: non-ambulant patients. Patients with a D1 MFM subscore ≤20 were classified as non-ambulatory [2]. Written informed consent was obtained from all patients or their

Results

All 20 patients had the MFM follow-up examination. 3/20 could not complete the MRI scanning protocol due to being unable to lie motionless in the scanner for the scanning period and 2/17 follow-up scans could not be analysed due to movement artefacts. 20/20 patients were included in the analysis of the clinical MFM scores aged 5–23 years at baseline (mean 14.9 years). 15 patients aged 5–17.8 years (mean 09.9) at baseline and 6–18.8 years (mean 10.9) at follow-up were included in the analysis of

Discussion

This prospective observational study compared functional parameters to quantitative MRI measures of fatty degeneration in assessing disease progression in DMD. The aim of this work was to test if the MFF acquired by a 2-PD technique can serve as a surrogate outcome measure in clinical trials in DMD. Power analysis was done to calculate the ES and SS needed in a clinical trial for both measurements.

For this study the key findings are:

  • -

    MFM D1 subscore showed the most significant decline in all

Acknowledgments

This study was supported by a grant from the Lorenzo-Piaggio Foundation, Switzerland. The sponsors had no influence on study design, data evaluation or publication. Ulrike Bonati: received funding from a research grant from the University of Basel. Patricia Hafner: received funding from a research grant from the University of Basel. Dr. Oliver Bieri has a research agreement with SIEMENS Medical Solutions. Dr. Arne Fischmann: was supported by a grant from Bracco, Switzerland. Dr. Dirk Fischer:

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    Both authors contributed equally to this work.

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