From fibre to function: are we accurately representing muscle architecture and performance?

Abstract

The size and arrangement of fibres play a determinate role in the kinetic and energetic performance of muscles. Extrapolations between fibre architecture and performance underpin our understanding of how muscles function and how they are adapted to power specific motions within and across species. Here we provide a synopsis of how this 'fibre to function' paradigm has been applied to understand muscle design, performance and adaptation in animals. Our review highlights the widespread application of the fibre to function paradigm across a diverse breadth of biological disciplines but also reveals a potential and highly prevalent limitation running through past studies. Specifically, we find that quantification of muscle architectural properties is almost universally based on an extremely small number of fibre measurements. Despite the volume of research into muscle properties, across a diverse breadth of research disciplines, the fundamental assumption that a small proportion of fibre measurements can accurately represent the architectural properties of a muscle has never been quantitatively tested. Subsequently, we use a combination of medical imaging, statistical analysis, and physics-based computer simulation to address this issue for the first time. By combining diffusion tensor imaging (DTI) and deterministic fibre tractography we generated a large number of fibre measurements (>3000) rapidly for individual human lower limb muscles. Through statistical subsampling simulations of these measurements, we demonstrate that analysing a small number of fibres (n < 25) typically used in previous studies may lead to extremely large errors in the characterisation of overall muscle architectural properties such as mean fibre length and physiological cross-sectional area. Through dynamic musculoskeletal simulations of human walking and jumping, we demonstrate that recovered errors in fibre architecture characterisation have significant implications for quantitative predictions of in-vivo dynamics and muscle fibre function within a species. Furthermore, by applying data-subsampling simulations to comparisons of muscle function in humans and chimpanzees, we demonstrate that error magnitudes significantly impact both qualitative and quantitative assessment of muscle specialisation, potentially generating highly erroneous conclusions about the absolute and relative adaption of muscles across species and evolutionary transitions. Our findings have profound implications for how a broad diversity of research fields quantify muscle architecture and interpret muscle function.

Anatomically grounded estimation of hindlimb muscle sizes in Archosauria

“…We were curious how consistently we measured fascicle lengths within our sampled muscles. Charles et al ( 2022 ) showed that small sample sizes of fascicle lengths can be poorly representative of architecture, having knock‐on effects for analysis of muscle function; our test partly addresses this concern. Different fascicle lengths throughout each muscle were measured at least three times on the same day by the same individual, following standard approaches (e.g.…”

“…Yet musculoskeletal models and simulations, which use such F max data, typically require muscle fascicle length estimates anyway; our PCSA:AA method does not circumvent that limitation. Relationships of muscle mass or PCSA with fascicle lengths in extant saurians are highly variable across muscles and can be variable within muscles (see Bates & Schachner, 2012 ; Bishop, Cuff, et al, 2021 ), so this is a significant challenge (also see Charles et al, 2022 ).…”

“…We were curious how consistently we measured fascicle lengths within our sampled muscles. Charles et al (2022) showed that small sample sizes of fascicle lengths can be poorly representative of architecture, having knock-on effects for analysis of muscle function;…”

“…3D imaging methods (CT and MRI scanning, etc. ) , so this is a significant challenge (also see Charles et al, 2022).…”

The association between muscle architecture and muscle spindle abundance

“…muscle fibre length and PCSA). Our novel approach relies on the curation of anatomical data, which we know to be highly variable, especially fibre length which is especially susceptible to error 26 . Additionally, while there is variability across the masses between our two data sets (Supplementary Table 1 ), the similarities in residual values between those derived from mass and from fibre length are encouraging and would in our opinion unlikely be a result of variability in the data.…”