AI Article Synopsis

  • The study explores how the shape of hamstring muscles could influence hamstring injuries, which has not been deeply studied before.* -
  • Researchers used statistical shape modeling (SSM) on MRI data from elite rugby players and track sprinters to compare hamstring muscle shapes.* -
  • Results showed that SSM could effectively distinguish muscle shape differences with high accuracy, suggesting it could aid future research on hamstring anatomy and injury prevention.*

Article Abstract

Hamstring morphology may play an important role in understanding the aetiology of hamstring injury. Currently, the methods available to capture detailed morphological data such as muscle shape have not been utilized for the hamstring muscles. The aim of this study was to examine the utility of statistical shape modelling (SSM) for describing and comparing hamstring muscle shape in rugby and sprinting athletes. Magnetic resonance images of both thighs of nine elite male rugby players and nine track and field sprinters were analysed. Images were converted to three-dimensional models enabling generation of four statistical shape models. Principal components describing the shape variation in the cohort were derived and evaluated. Six principal components were sufficient to discriminate differences in the shape of the hamstring muscles of rugby and sprinting athletes with 89% classification accuracy. Distinct shape features distinguishing rugby players from sprinters included size, curvature and axial torsion. These data demonstrate that SSM is useful for understanding hamstring muscle shape and that meaningful variation can be identified within a small sample. This method can be used in future research to enhance the anatomical specificity of musculoskeletal modelling and to understand the relationship between hamstring shape and injury.

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http://dx.doi.org/10.1080/02640414.2023.2204269DOI Listing

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