| dc.description.abstract | Duchenne muscular dystrophy (DMD) is a progressive myopathy caused by mutations in the dystrophin gene, leading to contraction-induced damage, inflammation, and necrosis in skeletal and cardiac muscles. Reliable methods of characterizing DMD cardiomyopathy are essential for effective pharmacological therapy. Myocardial circumferential strain (εcc) measured via harmonic phase (HARP) analysis is commonly used to measure cardiomyopathy. Heart rate variability (HRV) data can be used to quantify autonomic compensation in diseased patients, potentially providing an additional method of disease characterization. In this retrospective investigation, we hypothesized that 1) our custom HARP algorithm would be correlated with equivalent results from standard clinical software, and 2) that the εcc results would be correlated with HRV parameters. Twenty-eight boys with DMD were studied (ages 8-21). Cardiac MRI data included spatial modulation of magnetization (SPAMM)-tagged images, acquired throughout the cardiac cycle. HARP analysis was used to calculate peak Lagrangian εcc. Forty-eight-hour Holter monitoring data were acquired. Parasympathetic input-associate power (PIAP) was determined by spectral analysis of R-R intervals observed during sleep to determine the proportion of total power in the high-frequency band. The εcc results from our HARP algorithm were correlated with clinically-used values (r=0.79, p<1.0x10-7). PIAP measurements from two randomly sampled periods did not differ significantly (p=0.51) and had high reliability (intraclass correlation=0.923, p<0.001; n=28). However, PIAP did not prove to be a significant measure of disease characterization. Though promising patterns exist, key study limitations must be addressed in order to conclude that HRV parameters can provide an alternate method of assessing DMD. | |
