During childhood, muscle growth is stimulated by a gradual increase in bone length and body mass, as well as by other factors, such as physical activity, nutrition, metabolic, hormonal, and genetic factors. Muscle characteristics, such as muscle volume, anatomical cross‐sectional area, and muscle belly length, need to continuously adapt to meet the daily functional demands. Pediatric neurological and neuromuscular disorders, like cerebral palsy and Duchenne muscular dystrophy, are characterized by impaired muscle growth, which requires treatment and close follow‐up. Nowadays ultrasonography is a commonly used technique to evaluate muscle morphology in both pediatric pathologies and typically developing children, as it is a quick, easy applicable, and painless method. However, large normative datasets including different muscles and a large age range are lacking, making it challenging to monitor muscle over time and estimate the level of pathology. Moreover, in order to compare individuals with different body sizes as a result of age differences or pathology, muscle morphology is often normalized to body size. Yet, the usefulness and practicality of different normalization techniques are still unknown, and clear recommendations for normalization are lacking. In this cross‐sectional cohort study, muscle morphology of four lower limb muscles (medial gastrocnemius, tibialis anterior, the distal compartment of the semitendinosus, rectus femoris) was assessed by 3D‐freehand ultrasound in 118 typically developing children (mean age 10.35 ± 4.49 years) between 3 and 18 years of age. The development of muscle morphology was studied over the full age range, as well as separately for the pre‐pubertal (3–10 years) and pubertal (11–18 years) cohorts. The assumptions of a simple linear regression were checked. If these assumptions were fulfilled, the cross‐sectional growth curves were described by a simple linear regression equation. Additional ANCOVA analyses were performed to evaluate muscle‐ or gender‐specific differences in muscle development. Furthermore, different scaling methods, to normalize muscle morphology parameters, were explored. The most appropriate scaling method was selected based on the smallest slope of the morphology parameter with respect to age, with a non‐significant correlation coefficient. Additionally, correlation coefficients were compared by a Steiger's Z‐test to identify the most efficient scaling technique. The current results revealed that it is valid to describe muscle volume (with exception of the rectus femoris muscle) and muscle belly length alterations over age by a simple linear regression equation till the age of 11 years. Normalizing muscle morphology data by allometric scaling was found to be most useful for comparing muscle volumes of different pediatric populations. For muscle lengths, normalization can be achieved by either allometric and ratio scaling. This study provides a unique normative database of four lower limb muscles in typically developing children between the age ...
