Duchenne muscular dystrophy (DMD) is one of the most common neuromuscular diseases of children affecting approximately 1 in 3500 live male births, producing progressive muscle weakness and leaving affected individuals wheelchair bound by approximately 12 years of age with death occurring by the third decade of life. Over the past 20 years great inroads have been made into understanding the basic mechanisms underlying disease pathogenesis and many new potential therapeutic strategies have been developed, ranging from exon-skipping methodologies to stem cell therapies. This expanding range of disease treatment options has also greatly increased the need for improved methods to speed the assessment of promising drugs in Phase II and Phase III clinical trials. The current biomarkers that are employed, such as the 6-minute walk test, are relatively insensitive to change and require clinical trials to enroll large numbers of subjects while still being powered to detect an often overly optimistic treatment effect. Two highly innovative, easily applied, office-based, painless methodologies that offer great promise in serving as novel, sensitive markers of disease progression, are electrical impedance myography (EIM) and quantitative ultrasound (QUS). In EIM, a weak, high-frequency electrical current is applied via surface electrodes and alterations in the consequent surface voltage pattern are measured. In QUS, ultrasound images obtained using standard devices are distilled down to numerical data that can be used to quantify disease severity. This can be accomplished either via post-processing image analysis with use of a phantom for calibration or via a reduction of the raw backscattered acoustic data. In this proposed work, we will study both EIM and QUS independently to assess their potential use in DMD trials. Specifically we will do this by studying a group of 35 normal subjects and 35 boys with DMD aged 5 to 12 years followed for a 2-year period of time.
In Specific Aim 1, we will establish the repeatability of both techniques both immediately and over several days time.
In Specific Aim 2, we will assess the clinical significance of alterations in both EIM and QUS over time by comparing their rate of progression to that seen with functional measures out to two years.
In Specific Aim 3, we will assess the ability of both measures to detect disease progression over very short periods of time-1 to 2 months-and how well that rate of progression predicts long-term functional change. As part of our planned exploratory analyses, we will also assess approaches for fusing EIM and QUS data sets into single composite biomarkers and the potential value of following contraction-induced alterations in the EIM data over time. With the successful completion of this work, we will have set the stage for the use of one or both of these techniques as the preferred biomarkers in Phase II clinical trials in DMD.

Public Health Relevance

Clinical trials in Duchenne muscular dystrophy (DMD), one of the most common and devastating neuromuscular diseases of childhood, are limited by the fact that currently available biomarkers are relatively insensitive to assessing disease status and strongly dependent on subject cooperation. Two new techniques, electrical impedance myography and quantitative ultrasound, have shown great promise as novel, non- invasive, easily applied outcome measures in a variety of neuromuscular diseases. In this project we assess the value of these two techniques specifically in children with DMD. If successful, this work would lead to much faster and more efficient clinical trials, thus helping speed the identification of potentially effective therapies for this disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR060850-04
Application #
8718768
Study Section
Special Emphasis Panel (ZRG1-DTCS-U (81))
Program Officer
Nuckolls, Glen H
Project Start
2011-09-17
Project End
2015-07-31
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
4
Fiscal Year
2014
Total Cost
$403,956
Indirect Cost
$73,352
Name
Beth Israel Deaconess Medical Center
Department
Type
DUNS #
071723621
City
Boston
State
MA
Country
United States
Zip Code
02215
Zaidman, Craig M; Wu, Jim S; Kapur, Kush et al. (2017) Quantitative muscle ultrasound detects disease progression in Duchenne muscular dystrophy. Ann Neurol 81:633-640
Rutkove, Seward B; Kapur, Kush; Zaidman, Craig M et al. (2017) Electrical impedance myography for assessment of Duchenne muscular dystrophy. Ann Neurol 81:622-632
Koppaka, Sisir; Shklyar, Irina; Rutkove, Seward B et al. (2016) Quantitative Ultrasound Assessment of Duchenne Muscular Dystrophy Using Edge Detection Analysis. J Ultrasound Med 35:1889-97
Pigula, Anne J; Wu, Jim S; Gilbertson, Matthew W et al. (2016) Force-controlled ultrasound to measure passive mechanical properties of muscle in Duchenne muscular dystrophy. Conf Proc IEEE Eng Med Biol Soc 2016:2865-2868
Rutkove, Seward B; Wu, Jim S; Zaidman, Craig et al. (2016) Loss of electrical anisotropy is an unrecognized feature of dystrophic muscle that may serve as a convenient index of disease status. Clin Neurophysiol 127:3546-3551
Shklyar, Irina; Geisbush, Tom R; Mijialovic, Aleksandar S et al. (2015) Quantitative muscle ultrasound in Duchenne muscular dystrophy: a comparison of techniques. Muscle Nerve 51:207-13
Shklyar, Irina; Pasternak, Amy; Kapur, Kush et al. (2015) Composite biomarkers for assessing Duchenne muscular dystrophy: an initial assessment. Pediatr Neurol 52:202-5
Geisbush, Tom R; Visyak, Nicole; Madabusi, Lavanya et al. (2015) Inter-session reliability of electrical impedance myography in children in a clinical trial setting. Clin Neurophysiol 126:1790-6
Zaidman, Craig M; Wu, Jim S; Wilder, Sarah et al. (2014) Minimal training is required to reliably perform quantitative ultrasound of muscle. Muscle Nerve 50:124-8
Finkel, Richard S; McDermott, Michael P; Kaufmann, Petra et al. (2014) Observational study of spinal muscular atrophy type I and implications for clinical trials. Neurology 83:810-7

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