The National Institutes of Health (NIH) has awarded a $3.6M grant to support the Duchenne muscular dystrophy cardiac care consortium (DMDCCC). The consortium is working to integrate statistical modeling based on advanced imaging in order to improve the prediction of heart dysfunction, otherwise known as cardiomyopathy (CM). CM is the leading cause of death in Duchenne and Becker muscular dystrophy patients (DMD/BMD).

“The progression of cardiac disease is variable and poorly understood in DMD and BMD patients,” shares principal investigator Craig Goergen, PhD, Leslie A. Geddes Professor and Director of Clinical Programs at the Weldon School of Biomedical Engineering, Purdue University. “There are no blood or imaging biomarkers that can predict the pace of progression or the risk of early mortality in these patients. Given this and the variability between patients, clinical trials are challenging.”

The goal of the DMDCCC is to overcome those challenges in hopes of advancing the treatment of cardiac disease, and hopefully improving the quality of life for these pediatric patients.

The DMDCCC grant principal investigators include:

• Purdue University
  • Craig Goergen, PhD, Biomedical Engineering,
  • Guang Lin, PhD, Mathematics and Mechanical Engineering
• Riley Hospital for Children, Indiana University School of Medicine
  • Larry Markham, MD, Pediatric Cardiology
• Vanderbilt University Medical Center
  • Jonathan Soslow, MD, MSCI, Pediatric Cardiology
• Nationwide Children’s Hospital
  • Kan Hor, MD, Pediatric Cardiology

Each of the clinical sites offers similar cardiovascular treatment and diagnostic protocols, including cardiac magnetic resonance (CMR) imaging. With this award, the consortium will create a comprehensive registry of DMD/BMD patients with meticulously collected clinical data and CMR images. The major efforts to analyze patient image data and create algorithms capable of predicting progression will be led by Purdue University. Dr. Guang Lin, Professor of Mathematics, Mechanical Engineering, Statistics and EAPS at Purdue, will spearhead the efforts utilizing machine learning to analyze patient data.

“This study will create the largest cohort of patients, allowing a better understanding of cardiac disease progression and giving clinicians the ability to identify patients who are likely to have poor outcomes,” said Goergen. “The results will provide clinicians all over the world with a method to assess their patient’s risk in real time. This award from NIH will help expand our understanding of cardiac disease in pediatric patients, improving care for children with DMD.”

Research reported in this publication was supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number R01HL167969. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.”