Subject‐specific muscle properties from diffusion tensor imaging significantly improve the accuracy of musculoskeletal models

Abstract

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

Skeletal muscle function underpins muscle spindle abundance

“…Subject data were taken from Charles et al . [ 13 ], where 10 subjects were recruited (5 male and 5 female; age: 29 ± 3 years; body mass: 67.9 ± 9 kg; height- 175 ± 7 cm; BMI- 21.9 ± 1.6 kg m −2 ) and provided informed consent prior to participating in the study, in accordance with ethical approval from the University of Liverpool's Central University Research Ethics Committee for Physical Interventions (Reference no. : 3757).…”

“…For each muscle of the lower limb, these median muscle fibre length values from DTI were used to estimate optimal fibre length (L f ) through the normalization to a generic optimal sarcomere length [2.7 µm] [25]. See Charles et al [13] for more details regarding this normalization. These values were then used to calculate PCSA using the following formula:…”

“…These muscle architecture data informed lower limb musculoskeletal models actuated by 92 musculotendon units (MTUs), which were created for each of the 10 participants using NMSBUILDER software [26] and subsequently exported to OPENSIM 4.1 [27] (figure 1). For more details regarding the creation of these models from MRI, see [13]. Kinematic and kinetic data for walking at self-selected speeds from each individual (mean walking speed = 1.4 m s −1 ) were collected using a 12-camera motion capture system (Qualisys Inc., Göteborg, Sweden) and embedded force plates (Kistler, Winterthur, Switzerland).…”

“…This is in part due to the difficulty in collecting accompanying anatomical data in humans, as samples are largely derived from cadaveric preparations, and muscles being transversely sectioned limits additional morphometric measures that might be used to understand the causes and consequences of variations in spindle abundance. However, medical imaging and computational biomechanical models [ 13 ] provide a platform upon which to measure a of variety of anatomical metrics, and to predict functional musculoskeletal metrics that are impossible to measure in vivo . Together, these techniques therefore offer the opportunity to investigate the relationships between spindle abundance and other aspects of muscle anatomy (i.e.…”

Sensitivity of musculoskeletal models to variation in muscle architecture parameters

“…Continuing this work, Charles et al (2020) compared the accuracy of both subject-specific lower limb models and generic models built using data from both elderly and young individuals to muscle values obtained experimentally using an isokinetic dynamometer (Charles, Grant, Août, & Bates, 2020). Their results demonstrated that, while the generic models were not as accurate as the subject-specific models in predicting the experimental muscle values of particular individuals, generic models still have utility in musculoskeletal modelling studies.…”