title: Computational models predict larger muscle tissue strains at faster sprinting speeds.
abstract: BACKGROUND
  Proximal biceps femoris musculotendon strain injury has been well established as a common injury among athletes participating in sports that require sprinting near or at maximum speed; however, little is known about the mechanisms that make this muscle tissue more susceptible to injury at faster speeds.
  
  
  OBJECTIVE
  This study aimed to quantify localized tissue strain during sprinting at a range of speeds.
  
  
  METHODS
  Biceps femoris long head (BFlh) musculotendon dimensions of 14 athletes were measured on magnetic resonance (MR) images and used to generate a finite-element computational model. The model was first validated through comparison with previous dynamic MR experiments. After validation, muscle activation and muscle-tendon unit length change were derived from forward dynamic simulations of sprinting at 70%, 85%, and 100% maximum speed and used as input to the computational model simulations. Simulations ran from midswing to foot contact.
  
  
  RESULTS
  The model predictions of local muscle tissue strain magnitude compared favorably with in vivo tissue strain measurements determined from dynamic MR experiments of the BFlh. For simulations of sprinting, local fiber strain was nonuniform at all speeds, with the highest muscle tissue strain where injury is often observed (proximal myotendinous junction). At faster sprinting speeds, increases were observed in fiber strain nonuniformity and peak local fiber strain (0.56, 0.67, and 0.72 for sprinting at 70%, 85%, and 100% maximum speed). A histogram of local fiber strains showed that more of the BFlh reached larger local fiber strains at faster speeds.
  
  
  CONCLUSIONS
  At faster sprinting speeds, peak local fiber strain, fiber strain nonuniformity, and the amount of muscle undergoing larger strains are predicted to increase, likely contributing to the BFlh muscle's higher injury susceptibility at faster speeds.
authors.affiliation: 1Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA; 2Department of Biomedical Engineering, University of Virginia, Charlottesville, VA; 3Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI; 4Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI.
authors.forename: Niccolo M
authors.initials: NM
authors.lastname: Fiorentino
authors.forename: Michael R
authors.initials: MR
authors.lastname: Rehorn
authors.forename: Elizabeth S
authors.initials: ES
authors.lastname: Chumanov
authors.forename: Darryl G
authors.initials: DG
authors.lastname: Thelen
authors.forename: Silvia S
authors.initials: SS
authors.lastname: Blemker
mesh_terms: D001265:Athletic Injuries / Q000503:physiopathology; D003198:Computer Simulation; D003238:Connective Tissue / Q000503:physiopathology; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D018485:Muscle Fibers, Skeletal / Q000502:physiology; D018482:Muscle, Skeletal / Q000293:injuries* / Q000503:physiopathology*; D012420:Running / Q000502:physiology*; D013180:Sprains and Strains / Q000503:physiopathology*; D013710:Tendons / Q000503:physiopathology