In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging

Abstract

‘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.

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

“…Here, a similar method to that described previously (Charles et al ., 2019; Charles et al ., 2019) is used to estimate subject‐specific muscle architecture data from 31 muscles of the right lower limb from each subject. This involves the use of two MRI sequences, T1‐weighted anatomical turbo spin‐echo (TSE) to estimate muscle volumes and visualise muscle attachment points, and diffusion tensor imaging (DTI) to estimate muscle fibre lengths and pennation angles.…”

“… Generic young (GY) – Individualised musculoskeletal geometry with muscle force‐generating properties from young, healthy individuals (age – 28 ± 4 years; body mass – 71.9 ± 11 kg). This is a combined average of the data collected in the present study and a previously published in vivo data set collected using similar methods (Charles et al ., 2019). Relative to the elderly generic data, the muscles within this data set are characterised by higher muscle volumes and F max values, longer fibre lengths (particularly in more distal functional groups) and larger pennation angles (Figure 2).…”

“…Diffusion tensor imaging (DTI), a form of MRI, of skeletal muscle has recently emerged as a viable and repeatable method of obtaining muscle architecture in vivo (Bolsterlee et al ., 2019; Charles et al ., 2019), thereby circumventing traditional difficulties of obtaining estimates of individualised estimates of muscle force‐generating properties. The DTI technique has been shown to accurately visualise detailed in vivo anatomy within a variety of muscle groups (Froeling et al ., 2012; Sieben et al ., 2016; Bolsterlee et al ., 2018) within individuals of a variety of ages and with various pathologies (Malis et al ., 2019; Sahrmann et al ., 2019), as well as to build a novel data set of in vivo muscle architecture from young, healthy individuals (Charles et al ., 2019). However, despite its widespread use, how accurately these muscle data simulate individual muscle functions and overall biomechanical performance within subject‐specific musculoskeletal models relative to scaled or optimised generic data has not been tested.…”

Spatial-frequency Analysis of the Anatomical Differences in Hamstring Muscles

“…Direct comparisons about the proximo-distal variability in SM architectural is difficult to make since many studies have either measured from a single location or calculated the mean of several locations prior to subsequent analyses. 3,4,12,20,43 However, in two cadaveric studies, the pennation angle of the SM ( N = 8 limbs) was reported as 16 ± 2.4 degrees 3 and ( N = 22 limbs) 15.1 ± 3.4 degrees 4 with these measures calculated from the mean of proximal, middle, and distal locations along the SM. We calculated the whole muscle mean of pennation angle measures across all three locations along the SM as 15.4 ± 4.9 degrees, which is consistent with these previous studies.…”

Supervised segmentation framework for evaluation of diffusion tensor imaging indices in skeletal muscle

“…The analysis of DTI acquisitions requires many post‐processing steps for calculation of the DTI indices, which have been almost entirely automated—for more details see, eg, Reference 11 . However, segmentation of all the leg muscles, necessary for quantification, is a time‐consuming manual process, in which the accuracy and reproducibility may be operator dependent 12 .…”