Musculoskeletal modelling has become a valuable tool with which to understand how neural, muscular, skeletal and other tissues are integrated to produce movement. Most musculoskeletal modelling work has to date focused on humans or their close relatives, with few examples of quadrupedal animal limb models. A musculoskeletal model of the mouse hindlimb could have broad utility for questions in medicine, genetics, locomotion and neuroscience. This is due to this species’ position as a premier model of human disease, having an array of genetic tools for manipulation of the animal in vivo, and being a small quadruped, a category for which few models exist. Here, the methods used to develop the first three‐dimensional (3D) model of a mouse hindlimb and pelvis are described. The model, which represents bones, joints and 39 musculotendon units, was created through a combination of previously gathered muscle architecture data from microdissections, contrast‐enhanced micro‐computed tomography (CT) scanning and digital segmentation. The model allowed muscle moment arms as well as muscle forces to be estimated for each musculotendon unit throughout a range of joint rotations. Moment arm analysis supported the reliability of musculotendon unit placement within the model, and comparison to a previously published rat hindlimb model further supported the model's reliability. A sensitivity analysis performed on both the force‐generating parameters and muscle's attachment points of the model indicated that the maximal isometric muscle moment is generally most sensitive to changes in either tendon slack length or the coordinates of insertion, although the degree to which the moment is affected depends on several factors. This model represents the first step in the creation of a fully dynamic 3D computer model of the mouse hindlimb and pelvis that has application to neuromuscular disease, comparative biomechanics and the neuromechanical basis of movement. Capturing the morphology and dynamics of the limb, it enables future dissection of the complex interactions between the nervous and musculoskeletal systems as well as the environment.

Mice are one of the most commonly used laboratory animals, with an extensive array of disease models in existence, including for many neuromuscular diseases. The hindlimb is of particular interest due to several close muscle analogues/homologues to humans and other species. A detailed anatomical study describing the adult morphology is lacking, however. This study describes in detail the musculoskeletal geometry and skeletal muscle architecture of the mouse hindlimb and pelvis, determining the extent to which the muscles are adapted for their function, as inferred from their architecture. Using I2KI enhanced microCT scanning and digital segmentation, it was possible to identify 39 distinct muscles of the hindlimb and pelvis belonging to nine functional groups. The architecture of each of these muscles was determined through microdissections, revealing strong architectural specialisations between the functional groups. The hip extensors and hip adductors showed significantly stronger adaptations towards high contraction velocities and joint control relative to the distal functional groups, which exhibited larger physiological cross sectional areas and longer tendons, adaptations for high force output and elastic energy savings. These results suggest that a proximo-distal gradient in muscle architecture exists in the mouse hindlimb. Such a gradient has been purported to function in aiding locomotor stability and efficiency. The data presented here will be especially valuable to any research with a focus on the architecture or gross anatomy of the mouse hindlimb and pelvis musculature, but also of use to anyone interested in the functional significance of muscle design in relation to quadrupedal locomotion.

‘Gold standard’ reference sets of human muscle architecture are based on elderly cadaveric specimens, which are unlikely to be representative of a large proportion of the human population. This is important for musculoskeletal modeling, where the muscle force-generating properties of generic models are defined by these data but may not be valid when applied to models of young, healthy individuals. Obtaining individualized muscle architecture data in vivo is difficult, however diffusion tensor magnetic resonance imaging (DTI) has recently emerged as a valid method of achieving this. DTI was used here to provide an architecture data set of 20 lower limb muscles from 10 healthy adults, including muscle fiber lengths, which are important inputs for Hill-type muscle models commonly used in musculoskeletal modeling. Maximum isometric force and muscle fiber lengths were found not to scale with subject anthropometry, suggesting that these factors may be difficult to predict using scaling or optimization algorithms. These data also highlight the high level of anatomical variation that exists between individuals in terms of lower limb muscle architecture, which supports the need of incorporating subject-specific force-generating properties into musculoskeletal models to optimize their accuracy for clinical evaluation.

Musculoskeletal modelling is an important platform on which to study the biomechanics of morphological structures in vertebrates and is widely used in clinical, zoological and palaeontological fields. The popularity of this approach stems from the potential to non-invasively quantify biologically important but difficult-to-measure functional parameters. However, while it is known that model predictions are highly sensitive to input values, it is standard practice to build models by combining musculoskeletal data from different sources resulting in 'generic' models for a given species. At present, there are little quantitative data on how merging disparate anatomical

Accurate individualized muscle architecture data is crucial for generating subject-specific musculoskeletal models to investigate movement and dynamic muscle function. Diffusion tensor magnetic resonance (MR) imaging (DTI) has emerged as a promising method of gathering muscle architecture data in vivo, however its accuracy in estimating parameters such as muscle fiber lengths for creating subject-specific musculoskeletal models has not been tested. Here we provide a validation of the method of using anatomical MRI and DTI to gather muscle architecture data in vivo, by directly comparing those data obtained from MR scans of 3 human cadaveric lower limbs to those from dissections. DTI was used to measure fiber lengths and pennation angles, while the anatomical images were used to estimate muscle mass, which were used to calculate physiological cross-sectional area (PCSA). The same data were then obtained through dissections, where it was found that on average muscle masses and fiber lengths matched well between the two methods (4% and 1% differences respectively), while PCSA values had slightly larger differences (6%). Overall, these results suggest that DTI is a promising technique to gather in vivo muscle architecture data, but further refinement and complementary imaging techniques may be needed to realize these goals.