Human lower leg muscles grow asynchronously

Abstract

Muscle volume must increase substantially during childhood growth to generate the power required to propel the growing body. One unresolved but fundamental question about childhood muscle growth is whether muscles grow at equal rates; that is, if muscles grow in synchrony with each other. In this study, we used magnetic resonance imaging (MRI) and advances in artificial intelligence methods (deep learning) for medical image segmentation to investigate whether human lower leg muscles grow in synchrony. Muscle volumes were measured in 10 lower leg muscles in 208 typically developing children (eight infants aged less than 3 months and 200 children aged 5 to 15 years). We tested the hypothesis that human lower leg muscles grow synchronously by investigating whether the volume of individual lower leg muscles, expressed as a proportion of total lower leg muscle volume, remains constant with age. There were substantial age-related changes in the relative volume of most muscles in both boys and girls (p < 0.001). This was most evident between birth and five years of age but was still evident after five years. The medial gastrocnemius and soleus muscles, the largest muscles in infancy, grew faster than other muscles in the first five years. The findings demonstrate that muscles in the human lower leg grow asynchronously. This finding may assist early detection of atypical growth and allow targeted muscle-specific interventions to improve the quality of life, particularly for children with neuromotor conditions such as cerebral palsy.

Keywords: children; growth; lower leg muscles; magnetic resonance imaging; maturation.

FIGURE 1

Example scans, segmentation labels and 3D surface reconstructions of lower leg muscles and bones of (a‐c) an infant aged 2 months and (d‐f) a child aged 11 years. (a and d) Transverse slice of an mDixon water image, approximately mid‐way between the knee and ankle joint, with segmentation labels overlayed in the right panel. (b and e) Transverse slice of a T1‐weighted image, same slice levels as the mDixon images in a and d, with segmentation labels overlayed in the right panel. (c and f) Posterior and anterior views of the 3D surface models.

FIGURE 2

Relationship between the absolute volume of each muscle and age (left panel) and tibia length (right panel). Lines are penalised cubic regression splines. Abbreviations for muscle groups are given in Figure 1.

FIGURE 3

Relationship between the relative volume of each muscle and age (left panel) or tibia length (right panel). Lines are penalised cubic regression splines. Abbreviations for muscle groups are given in Figure 1.