Large-scale study of the hip, knee, and ankle reveals sex and angle-dependent muscle volume and torque scaling relationships.

Garcia, Mario E; McCain, Emily; Hu, Xiao; Steininger, Kimberly M; Knizley, Amanda; Burke, Hudson; Luk, Allen; Shea, Brendan S et al. · J Biomech · 2026

cross_sectional · Level IV

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Abstract

Characterization of the relationship between muscle size and torque has a strong theoretical foundation and is supported by empirical evidence. However, the relationships between muscle morphology and force generation remain incomplete. Previous MRI-based studies linking structure and function have been limited by small, male-dominant samples, reducing generalizability. Expanding datasets that integrate MRI-derived muscle volumes and torque across multiple joints, angles, and sexes is essential to advance biomechanical understanding of human strength. To address this, the present study quantified how MRI-derived muscle group volumes scale with peak isometric joint torque across a range of angles, developed robust regression models linking these variables, and established a normative, sex-balanced reference dataset of paired volumetric and torque measurements. A cohort of 103 healthy adults (55 females, 48 males) underwent MRI and dynamometry testing across eight lower-limb exertions. Muscle-group volume correlated strongly with height-mass index (R<sup>2</sup> = 0.69-0.81, p < 0.05), with a significant sex effect. Peak torque additionally correlated with height-mass index (R<sup>2</sup> = 0.11-0.61, p < 0.05), with a significant sex effect in all but plantar flexion. Muscle group volume significantly predicted peak torque across all exertion-angle combinations (R<sup>2</sup> = 0.19-0.78, p < 0.05), with ankle dorsiflexion showing the strongest correlations. Sex had a significant effect at the hip when characterizing the muscle-group volume and peak torque relationship. Sex-specific differences in residual torque from a sex-agnostic generalized model reinforce the need for sex-specific regressions. This dataset provides a comprehensive reference of lower-limb muscle volumes and torque, offering regression formulas to improve model accuracy, address sex-specific scaling, and support comparisons across age and disease groups.

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