Multi-parametric quantitative MRI of the lower limb muscles in a longitudinal study of limb-girdle muscular dystrophy R9.
Objective: Limb-girdle muscular dystrophy R9 (LGMD-R9) is a rare neuromuscular disease with no curative treatment. Sensitive non-invasive biomarkers are necessary to monitor disease progression and evaluate the efficacy of novel therapies. Here, we investigated several quantitative MRI parameters as suitable biomarkers for evaluating disease progression in LGMD-R9.
Methods: Bilateral quantitative MRI of the lower limbs was performed in individuals with LGMD-R9 and healthy controls. Quantitative thigh and leg muscle MRI, functional tests (including time-up-and-go (TUG) and time-to-climb-4-stairs (4S climb)), and muscle strength tests were performed in individuals with LGMD-R9 at baseline, 1-year, and 2-years. qMRI included assessment of muscle fat fraction (FF), water T2, water T1, intramuscular pH from 1H MR spectroscopy, and diffusion tensor imaging (DTI) parameters. Differences between LGMD-R9 and controls, over time, and the relationship between baseline water T1 and water T2 parameters and disease progression (FF, functional and strength parameters) were assessed by linear mixed models and correlation analyses.
Results: 18 individuals with LGMD-R9 and 13 controls were enrolled. At baseline, elevated FF, water T2, water T1, and pH were observed in LGMD-R9 (p < 0.05). No differences between controls and LGMD-R9 were found in the DTI parameters. An overall tendency to an increase in FF and a decrease in functional measures were observed over 2 years. However, the changes did not reach significance (p = 0.057-0.752). Baseline water T1 and baseline water T2 correlated with the increase in FF (ΔFF) and change in TUG (ΔTUG) and 4S climb (Δ4S climb) over 2 years (correlation coefficient ≥ 0.6, p < 0.05). No correlation with the strength measures was found.
Conclusions: Our findings suggest that FF, water T2, water T1, and pH are effective biomarkers for LGMD-R9. The correlation of water T2 and water T1 with ΔFF, ΔTUG, and Δ4S climb suggests their potential in predicting disease progression.