Introduction Athletes use their skeletal muscles to demonstrate performance. Muscle force generating capacity is correlated with volume, meaning that variations in sizes of different muscles may be indicative of how athletes meet different demands in their sports. Medical imaging enables in vivo quantification of muscle volumes; however, muscle volume distribution has not been compared across athletes of different sports. Purpose The goal of this work was to define "muscular phenotypes" in athletes of different sports and compare these using hierarchical clustering. Methods Muscle volumes normalized by body mass of athletes (football, baseball, basketball, or track) were compared with control participants to quantify size differences using z-scores. z-Scores of 35 muscles described the pattern of volume deviation within each athlete`s lower limb, characterizing their muscular phenotype. Data-driven high-dimensional clustering analysis was used to group athletes presenting similar phenotypes. Efficacy of clustering to identify similar phenotypes was demonstrated by grouping athletes` contralateral limbs before other athletes` limbs. Results Analyses revealed that athletes did not tend to cluster with others competing in the same sport. Basketball players with similar phenotypes grouped by clustering also demonstrated similarities in performance. Clustering also identified muscles with similar volume variation patterns across athletes, and principal component analysis revealed specific muscles that accounted for most of the variance (gluteus maximus, sartorius, semitendinosus, vastus medialis, vastus lateralis, and rectus femoris). Conclusions Athletes exhibit heterogeneous lower limb muscle volumes that can be characterized and compared as individual muscular phenotypes. Clustering revealed that athletes with the most similar phenotypes do not always play the same sport such that patterns of muscular heterogeneity across a group of athletes reflect factors beyond their specific sports.
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