The first reports of the findings of the MUGgLE study have been published in scientific journals and in conferences. This page gives an overview of the published findings to date.
Muscle size and structure in infants
While the majority of MUGgLE participants are children aged 5 to 15 years, we also scanned the legs of eight infants under 3 months of age. These scans provided the most detailed information to date of the size and structure of human muscles shortly after birth. One finding was that, while calf muscles in adults are ~63 times the size of infants’ muscles, the muscle fascicles are only 1.7 times longer. (Muscle fascicles are bundles of muscle cells or fibres that extend from one end of the muscle to the other.) This shows that, between infancy and adulthood, muscle growth primarily involves an increase in muscle fascicle cross-section rather than an increase in muscle fascicle length.
Read more in our publication in the Journal of Biomechanics.
Lower leg muscles grow at different rates
Using the first scans obtained from the 208 typically developing infants and children in the MUGgLE study, we investigated how the size of 10 lower limb muscles changes during childhood development. Specifically, we looked at whether these muscles grow at equal rates. In other words, we asked if the muscles of a 5-year old are simply scaled-up version of infants’ muscles, and scaled-down versions of a 15-year old’s muscles? The answer was ‘no’: lower leg muscles grow at different rates. For example, in infants 2-3 months of age, the largest muscle in the calf (the soleus) takes up ~22% of the volume of all lower leg muscles combined, and that increases to ~30% in children aged 5. The findings that some muscles grow relatively faster than others may have implications for understanding disordered muscle growth in children with cerebral palsy.
Read more in our publication in the Journal of Anatomy.
Artificial intelligence to the rescue!
The enormous amount of MRI scans obtained for the MUGgLE study presented us with a practical challenge: how to analyse the data efficiently and to the highest standard possible within a reasonable timeframe. The most time-consuming step is outlining structures of interest on the images. For the MUGgLE study this meant that muscles needed to be outlined (“coloured in”) on all slices of all scans – about 200,000 images! We calculated that would take us >700 working days. Luckily, in collaboration with computer scientists at UNSW, we developed highly accurate automated methods using the latest advances in artificial intelligence. The results meant that we can now “colour in” muscles from our MRI scans within seconds, rather than in 8-10 hours per scan!
Read more in our publication in NMR in Biomedicine.