Statistical shape modelling reveals differences in hamstring morphology between professional rugby players and...

Area of Science:

• Biomechanics
• Sports Medicine
• Anatomy

Background:

• Hamstring injuries are common in athletes.
• Understanding hamstring muscle morphology is crucial for injury prevention.
• Current methods lack detailed shape analysis for hamstring muscles.

Purpose of the Study:

• To assess the utility of statistical shape modelling (SSM) for characterizing hamstring muscle shape.
• To compare hamstring muscle morphology between elite rugby players and sprinters.
• To explore the potential of SSM in understanding hamstring injury aetiology.

Main Methods:

• Magnetic resonance imaging (MRI) of hamstring muscles from nine rugby players and nine sprinters.
• Conversion of MRI data into 3D models.
• Generation and analysis of four statistical shape models to identify principal components of shape variation.

Main Results:

• Six principal components adequately discriminated hamstring shapes between athlete groups with 89% accuracy.
• Key distinguishing features included muscle size, curvature, and axial torsion.
• SSM identified meaningful shape variations even within a small sample size.

Conclusions:

• Statistical shape modelling is a valuable tool for analyzing hamstring muscle morphology.
• Significant differences in hamstring shape exist between rugby and sprinting athletes.
• This method can enhance musculoskeletal modelling and injury research by providing anatomical specificity.